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The overall goal of this paper is to assess the potential of fully polarimetric SAR data for land-use mapping in the field of ecosystem monitoring. State of the art ecosystems' studies aim at integrating in-situ measurements acquired by smart sensor networks with Earth observation data analysis to ensure data quality services to multiple applications. The near real time observation using optical and...
Synthetic Aperture Radar (SAR) Tomography is a multi-temporal technique which can reconstruct the 3D profile of a scene. One of its main features consists in the ability to detect the presence of multiple Persistent Scatterers (PS) within the same resolution cell. This paper aims to investigate the super-resolution capabilities of SAR Tomography, by detecting targets situated at a distance which is...
Ground-based fixed receiver bistatic synthetic aperture radar (SAR) is a technology increasingly used in urban monitoring, complementing and enriching the traditional monostatic SAR, but the acquisition geometry is more complex than in the monostatic case. Hence, in the design and configuration of real bistatic SAR systems simulations are needed. In this regard we have presented in [1] a simulator...
An effective monitoring and analysis of ecosystems requires developing new tools and knowledge. In this paper, we propose an approach for detecting land-cover changes using satellite Image Time Series. This approach represents each image by spectral indices and then extracts local features of these representations. Next, a clustering technique (e.g., k-means) is applied to the extracted features,...
In the quest of developing more accurate methodologies for Earth Observation (EO) image retrieval, visualization and information content exploration, a deep understanding of the data being analyzed is needed. In this paper we propose a simple but efficient visual data mining methodology that can be used for these tasks. Our solution consists in a patch-based feature extraction to derive image features...
This paper presents results obtained by applying the maximum entropy method to image reconstruction of C-band ground-based synthetic aperture radar images. In GB-SARs, azimuth resolution is dependent on the range to target. Hence, a range dependent point spread function is synthesized. Experimental results show that through the maximum entropy method target detection is enhanced resulting in both...
This paper makes an analysis of repeat-pass bistatic synthetic aperture radar (SAR) interferometry performed with a stationary ground-based receiver and a satellite as transmitter of opportunity. A numerical approach is developed in order to asses the sensitivity of the repeat-pass across-track bistatic interferometric phase to height (relative to the digital elevation model used for focusing) and...
In the era of constantly increasing Earth Observation (EO) data collections, information extraction and data analysis should be enhanced with a multi-temporal component enabled by the temporal resolution of satellite missions and create handy, yet powerful tools for those applications involving monitoring of land cover. The image time series, as results of the satellite revisiting period, gives you...
Some of the first Earth Observation (EO) missions date back to the 1970s. Over the time, large datasets of Satellite Image Time Series (SITS) have been used to identify and monitor land cover evolutions. The processing complexity increases proportionally to the time span of the Earth Observation (EO) series. Because of the SITS dataset complexity and variety of contained evolution patterns, most unsupervised...
Current satellite images and image time series provide us with detailed information about the state of our planet as well as about our technical infrastructure and human activities. These images allow us to learn more about local, regional, and global phenomena and events, including - if interpreted properly - their causes and effects. In particular, image time series provide specific information...
Satellite Image Time Series (SITS) are widely used in monitoring the Earth's changes for various applications such as land-cover evolution analysis. In this paper, we propose an approach based on Latent Dirichlet Allocation (LDA) which considers spatial and spectral information to measure the land-cover changes in multispectral SITS. For our experiments, we focus on the vegetation dynamics of the...
In this paper, we propose a bistatic synthetic aperture radar (SAR) imaging procedure using a Sentinel-1 satellite as transmitter of opportunity and a stationary ground receiver. The procedure is designed for the standard operating mode of Sentinel-1 satellites - Terrain Observation with Progressive Scans SAR (TOPSAR) and essentially comprises the synchronization between satellite transmitter and...
This paper investigates different multi-scale approaches in terms of feature extraction for classification of interfero-metric SAR (InSAR) and previously defined phase gradient InSAR (PGInSAR) images. For this purpose, the scale-space image representation approach is implemented together with the two partial derivative based structure matrices, namely the Hessian matrix and second moment matrix. Their...
This paper proposes a custom convolutional deep belief network for polarimetric synthetic aperture radar (PolSAR) data feature extraction. The proposed architecture stands out through the interesting features it shows, starting with the fact that it is adapted to fully polarimetric SAR data. Then, the multilayer approach allows the stepwise discovery of higher-level features. The convolutional approach...
The lack of a comprehensive solution for image information mining has often brought confusion and misunderstanding when Earth Observation data based application scenarios were addressed. Considering the variety of dedicated sensors available nowadays, the particularities of the recorded data raises serious issues when explored. Most of the proposed methodologies for data analysis integrate algorithms...
In this paper we present the early development of a SAR simulator for ground-based fixed-receiver bistatic geometry. Firstly, we describe the assumptions the simulator is based on, then a short presentation of the mathematical model that lays behind the simulator is given. Furthermore, we give some details about its implementation and finally, we present some results.
In this paper, we present the visualization of image databases based on their primitive features. Our approach is to have a visual navigation tool for allowing the exploration and exploitation of large image archives. The tool is able to project the content of a given image database based on the primitive feature space and to provide interaction between the final user and the huge amount of data....
The main advantage of Synthetic Aperture Radar (SAR) Tomography over classical interferometry consists in capacity to detect the presence of multiple scatterers within the same resolution cell. In this paper we present an algorithm for detection of Persistent Scatterers (PS) based on the variation of reflectivity function in elevation direction reconstructed with Beam-Forming technique. Then, we extract...
The data mining systems solve the problem of handling Earth Observation archives counting on a feature vectors based description of the data. Increasing the dimensionality of the feature vectors would offer an effective perspective of the dataset's content. The modern systems provide visual exploration of data projecting their high-dimensional feature space in a 3-D space. The dimensionality reduction...
This paper presents the first SAR imaging results obtained with a fixed ground-based system used in bistatic configuration having the TerraSAR-X satellite as transmitter of opportunity. The system's characteristics and signal processing flow are presented relative to the state of the art. Compared to previous works on bistatic SAR imaging where a significant amount of processing is dedicated to time/frequency...
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